1760 search results - page 6 / 352 » Gene set analysis using principal components |
BMCBI
2007
13 years 8 months ago
2007
Background: When analyzing microarray gene expression data, missing values are often encountered. Most multivariate statistical methods proposed for microarray data analysis canno...
ICPR
2006
IEEE
14 years 9 months ago
2006
IEEE
In this paper, a multilinear formulation of the popular Principal Component Analysis (PCA) is proposed, named as multilinear PCA (MPCA), where the input can be not only vectors, b...
ICRA
1998
IEEE
14 years 8 days ago
1998
IEEE
1 sensors is to construct a structural description from sensor data and to match this description to a previously acquired model [Crowley 85]. An alternative is to project individu...
ICCV
2001
IEEE
14 years 10 months ago
2001
IEEE
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
JMLR
2010
13 years 2 months ago
2010
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...